AI Governance

The system flags, prioritizes, and explains. People decide.

Stream Engine builds intelligence tools for military, law enforcement, investigators and private sector. Our AI reads content, applies rules that people write, and drafts summaries grounded in the record. It never takes action on its own. Four commitments shape every product we build.

Accountability

Every output traces back to a person, a rule, or a model version.

• Our systems never take action against an account, reach out to anyone being monitored, or act on a case by themselves.
• Every correction requires a reason, and the original machine output stays on record.
• An append-only audit trail records who did what and when, and which model and rule versions were used. That includes the work of our own staff.
• Evidence is hashed at capture and stored write-once, so anyone can verify its integrity independently.

Transparency

Anyone who relies on an output can see why it exists.

• Flags come from plain-language rules, and each one points to the exact text, image region, or timestamp that triggered it.
• AI-generated content is labeled and cites the records it draws on.
• Where we rank work, the score breaks down into its parts, and the parts add up to the total.
• Every run reports what was and was not analyzed, so an empty result is never mistaken for a clean one.

Fairness

The same rules apply to every item in the same way.

• We do not compute risk scores for people.
• We do not use facial recognition or biometric matching to identify anyone.
• Every active rule runs on every item in scope, and model versions change only through a controlled release.
• Investigators can reject any reading with a reason, and we measure how often our readings are corrected.

Responsibility

We limit what we collect and what the system can do.

• We collect only public content, through approved sources and within each platform’s terms, or analyze records our customers lawfully hold and provide.
• Every project has a stated purpose and a set time window, and collection stays inside both.
• Data is encrypted in transit and at rest, kept on a set retention schedule, and deleted with a logged record.
• Real customer data is loaded only after governance, evidence, and security controls are in place.